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Abstract Details
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Activity Number:
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400
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Physical and Engineering Sciences
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| Abstract - #305669 |
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Title:
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Uniform Fractional Factorial Designs
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Author(s):
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Hongquan Xu*+ and Yu Tang and Dennis Lin
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Companies:
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University of California at Los Angeles and Soochow University and Penn State University
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Address:
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Department of Statistics, Los Angeles, CA, 90095-1554, United States
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Keywords:
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Discrepancy ;
generalized minimum aberration ;
generalized wordlength pattern ;
geometrical isomorphism ;
uniform minimum aberration design
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Abstract:
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The minimum aberration criterion has been frequently used in the selection of fractional factorial designs with nominal factors. For designs with quantitative factors, however, level permutation of factors could alter their geometrical structures and statistical properties. In this paper uniformity is used to further distinguish fractional factorial designs, besides the minimum aberration criterion. It is showed that minimum aberration designs have low discrepancies on average. An efficient method for constructing uniform minimum aberration designs is proposed and optimal designs with 27 and 81 runs are obtained for practical use. These designs have good uniformity and are effective for studying quantitative factors.
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